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This article introduces several common image file formats such as BMP, PNG, JPEG, TIFF, WebP, and others, explains their typical use cases, and provides Python OpenCV code snippets for reading, displaying, and saving images in each format.
iQIYI optimized its app’s visual experience by progressively replacing JPG with WebP, HEIC, and finally AVIF—using a caplist‑driven CDN, self‑developed decoders and on‑demand production pipelines—to cut image sizes, reduce CDN bandwidth by over 30 % and maintain quality across static, transparent and animated assets.
This article explains why image resources dominate front‑end performance, describes how binary depth relates to color representation, compares common image formats (JPEG, PNG‑8/24, SVG, WebP, Base64), and provides practical techniques such as compression tools, CDN/OSS deployment, and lazy‑loading code to dramatically improve page load speed.
The article traces the history from early Live CD technologies like Knoppix’s cloop and SquashFS, through the development of union filesystems such as aufs, to Docker’s layered image model, and discusses emerging next‑generation image formats aiming to reduce redundancy and improve lazy loading.
To address the slow loading and high bandwidth costs of GIFs in short‑content feeds, the team evaluated APNG, WebP, SharpP, and MP4, found MP4 video conversion offers the best compression, universal support and comparable CPU usage, achieving a 62% size reduction, 90% instant‑open rate and a 5.6% exposure boost.
The article defines dynamic image formats, traces their history from GIF to WebP, compares GIF, APNG and WebP features and Android decoding performance, showing WebP offers smaller files and faster loading at higher CPU cost, while GIF remains most compatible and CPU‑efficient.